The Semantic Web
We stand in the midst of what is often referred to as Web 2.0, with Google responding to the explosion of multi-media by giving significant ranking factor for its mere inclusion, even though indexing bots can hardly discern what it contains.
Even getting a bot to understand the text contents of a simple HTML page is often challenging enough.
As today’s consumers demand to be served increasingly more accurate results from a search engine query, we find ourselves rushing headlong into the Semantic Web.
For those of you who do not know, the Semantic Web is an evolving extension of our current web, in which the semantics of information is defined, making it possible for bots to “intuit” data and therefore, for Google to satisfy requests for content with far greater accuracy.
The Semantic Web is capable of accurately answering search requests by employing natural language processing systems capable of converting samples of human language into more formal representations that are easier for computer programs to manipulate.
Our current search engines rely on a less rigid representation of natural language where latent semantic indexing and co-occurrence matrices are utilized to find patterns.
Latent semantic analysis is a technique of natural language processing in which relationships between a set of documents and the terms they contain are analyzed. It produces a set of concepts related to the documents and terms.
While this has been, to date, surprisingly effective, this analysis is limited because the very data that it attempts to understand has been constructed by inconsistent means. Natural inconsistencies between people and cultures create a body of work in which the language is simply not rigorous enough to allow computers to discern a significant amount of meaning.
The semantic web will go further than latent semantic analysis could ever take us.
The foundation of the semantic web is comprised of a set of design principles and enabling technologies. Some examples of these include Resource Description Framework (RDF), a variety of data exchange formats (e.g. RDF/XML, N3, Turtle, N-Triples), and notations such as RDF Schema (RDFS) and the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms and relationships within a particular field of knowledge, or domain.
An ontology is a formal representation of a set of concepts within a domain and the relationships between those concepts. It is used to understand and reason about the properties of that domain, and may be used to define the domain. Ontologies are used as a form of knowledge representation about the world or some part of it.
As an ontology defines the concepts and relationships within a domain, it provides a standardized vocabulary for that domain and the relationships between those concepts. The standardization creates a specification which allows a computer to understand the vocabulary. Ontologies range from simple taxonomies and classifications, to database schemas, and on to fully axiomatized theories.
In recent years, ontologies have been adopted in many business and scientific communities as a way to share, reuse and process domain knowledge. Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce, and semantic web services.
Tim Berners-Lee originally expressed the vision of the semantic web as follows:
”I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize.”
- Tim Berners-Lee, 1999
Available today are an ever growing number of applications which attempt to realize this vision either through a top-down or a bottom-up approach to web semantics.
A plausible definition of a "semantic application" is one that has a core element which attempts to determine the meaning of text and other data, and then attempts to create previously unassociated connections or relationships for users.
Data portability and connectivity are keys to the new semantic applications. What is evolving is not going to be just Google with better search results, but rather a search engine that answers your question and then associates references for more information and connects tangent ideas and related activities.
The foundation principle behind Theme Zoom's Krakken application is the idea of "theming" your web pages and your website so that your themes and the prominent ideas that comprise your themes are easily recognizable to the search engines.
These themes are established by the relationships between Keywords highlighted on inter-linking pages. The interlinking pages referred to here are both those within your website and those external web pages to which, and from which your web pages link. The topics of these pages and the manner in which they connect, create the relationships, and hence the themes.
These themes, properly defined, will become the very cornerstones of the relationships in the Semantic Web. While the expression utilized to document these themes and their relationships may be enhanced over the coming months, properly choosing the main themes of your website will serve you well now and into the future.